An escalator vibration trend prediction method based on big data comprises the steps of collecting multi-path big data information of an escalator, separating independent component information, reconstructing pure vibration source signal features after filtering, correspondingly constructing an escalator vibration data set, establishing a recognition model, carrying out working condition judgment, and predicting the escalator vibration trend. According to the method, the problems that interference of a high-noise environment and multi-working-condition escalator trend mixing are difficult to independently extract, trend sequence prediction is accurate and the like can be solved, and the escalator vibration trend can be effectively predicted.
一种基于大数据的扶梯振动趋势预测方法,包括收集扶梯多路大数据信息,分离各独立成分信息,滤波后重构纯净的振动源信号特征,对应构建扶梯振动数据集,建立识别模型并进行工况判别,对电动扶梯振动趋势进行预测,该方法可解决了高噪声环境的干扰和多工况扶梯趋势杂混难以独立提取,趋势序列预测准确等问题,能对扶梯振动趋势进行有效的预测。
Escalator vibration trend prediction method based on big data
一种基于大数据的扶梯振动趋势预测方法
2023-04-04
Patent
Electronic Resource
Chinese
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